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花生废弃物中白藜芦醇和白藜芦醇苷的提取与定性定量分析

, PP. 46-50

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Abstract:

采用HPLC法从珍珠红14、粤油114、汕油523和湛油75等4个品种花生的废弃物中提取白藜芦醇和白藜芦醇苷，并进行定性与定量分析，根据提取物的HPLC出峰时间及与对照品的相加试验，在4个花生品种的不同器官中均鉴定出了白藜芦醇和白藜芦醇苷.不同花生品种和同一品种不同器官中2种活性物质的含量差异很大；在珍珠红14的各器官中含量最高，湛油75中含量最低.各品种花生根中2种化合物的含量最高.珍珠红14的根、茎、叶和果壳中白藜芦醇含量分别为148.7、33.3、23.1和9.4μg/g，白藜芦醇苷含量分别为133.7，37.7，27.7和11.5μg/g.珍珠红14根中白藜芦醇和白藜芦醇苷含量大大高于葡萄和桑椹等材料.本研究为花生废弃物的综合利用提供了依据.

 References

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[29]  Jung C R, Kelber C R.A lane departure warning system using lateral offset with uncalibrated camera[C]//IEEE Proceedings of the International Conference on Intelligent Transportation Systems.Vienna,2005:348-353
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[31]  陈军.基于DSP的高速公路车道偏离报警系统研究[D].天津大学,2010
[32]  Hsiao P Y,Yeh C W,Huang S S.A Portable Vision-Based Real-Time Lane Departure Warning System: Day and Night[J].IEEE Trans on Vehicular Technology,2009,58(4):2089-2094
[33]  Tseng S P,Liao Y S, Yeh C H.A DSP-based lane recognition method for the lane departure warning system of smart vehicles[C]//International Conference on Networking, Sensing and Control(ICNSC09).Okayama,Japan,2009:823–828
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[35]  MMcCall J C,Trivedi M M.Video-based Lane Estimation and Tracking for Driver Assistance:Survey,System, and Evaluation[J].IEEE Trans on Intelligent Transportation Systems,2006,7(1):20-37
[36]  Assidiq A A,Khalifa O O,Islam M R,et al.Real Time Lane Detection for Autonomous Vehicles[C] //International Conference Computer and Communication Engineering (ICCCE).Kuala Lumpur,Malaysia,2008:82–88
[37]  Jeong S G, Kim C S, Yoon K S, et al.Real-time Lane Detection for Autonomous Navigation[C]//IEEE Proceedings of Intelligent Transportation Systems (ITSC01). Oakland,USA,2001:508–513
[38]  MMcCall J C,Trivedi M M.Video-based Lane Estimation and Tracking for Driver Assistance:Survey,System, and Evaluation[J].IEEE Trans on Intelligent Transportation Systems,2006,7(1):20-37
[39]  Assidiq A A,Khalifa O O,Islam M R,et al.Real Time Lane Detection for Autonomous Vehicles[C] //International Conference Computer and Communication Engineering (ICCCE).Kuala Lumpur,Malaysia,2008:82–88
[40]  Hsiao P Y,Yeh C W,Huang S S.A Portable Vision-Based Real-Time Lane Departure Warning System: Day and Night[J].IEEE Trans on Vehicular Technology,2009,58(4):2089-2094
[41]  Tseng S P,Liao Y S, Yeh C H.A DSP-based lane recognition method for the lane departure warning system of smart vehicles[C]//International Conference on Networking, Sensing and Control(ICNSC09).Okayama,Japan,2009:823–828
[42]  LLee J W.A Machine Vision System for Lane-Departure Detection[J].Computer Vision and Image Understanding,2002,86(1):52-78
[43]  李李旭, 张为公.基于视觉的车道偏离报警系统的研究[J].仪器仪表学报,2008,(7):1554-1558
[44]  Kim S Y,Oh S Y.A driver adaptive lane departure warning system based on image processing and a fuzzy evolutionary technique[C]//IEEE Intelligent Vehicles Symposium.Columbus,USA,2003:361-365
[45]  Jung C R, Kelber C R.A lane departure warning system using lateral offset with uncalibrated camera[C]//IEEE Proceedings of the International Conference on Intelligent Transportation Systems.Vienna,2005:348-353
[46]  Jeong P,Nedevschi S.Efficient and robust classification method using combined feature vector for lane detection[J].IEEE Trans on Circuits and Systems for Video Technology.2005,15(4):528-537
[47]  陈军.基于DSP的高速公路车道偏离报警系统研究[D].天津大学,2010
[48]  Hsiao P Y,Yeh C W,Huang S S.A Portable Vision-Based Real-Time Lane Departure Warning System: Day and Night[J].IEEE Trans on Vehicular Technology,2009,58(4):2089-2094
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[53]  Jung C R, Kelber C R.A lane departure warning system using lateral offset with uncalibrated camera[C]//IEEE Proceedings of the International Conference on Intelligent Transportation Systems.Vienna,2005:348-353
[54]  Jeong P,Nedevschi S.Efficient and robust classification method using combined feature vector for lane detection[J].IEEE Trans on Circuits and Systems for Video Technology.2005,15(4):528-537
[55]  陈军.基于DSP的高速公路车道偏离报警系统研究[D].天津大学,2010

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